wx44wx/pipecat
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

DailyRESTHelper now receives an aiohttp client session

Browse Source
This commit is contained in:
Aleix Conchillo Flaqué
2024-08-01 18:08:57 -07:00
parent 8263d1dd6f
commit 4d9b7cdd61
51 changed files with 647 additions and 516 deletions
Download Patch File Download Diff File Expand all files Collapse all files

95
examples/foundational/07e-interruptible-playht.py
View File

@@ -4,6 +4,7 @@
# SPDX-License-Identifier: BSD 2-Clause License
#
import aiohttp
import asyncio
import os
import sys
@@ -31,62 +32,64 @@ logger.add(sys.stderr, level="DEBUG")
async def main():
(room_url, token) = await configure()
transport = DailyTransport(
room_url,
token,
"Respond bot",
DailyParams(
audio_out_enabled=True,
audio_out_sample_rate=16000,
transcription_enabled=True,
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer()
async with aiohttp.ClientSession() as session:
(room_url, token) = await configure(session)
transport = DailyTransport(
room_url,
token,
"Respond bot",
DailyParams(
audio_out_enabled=True,
audio_out_sample_rate=16000,
transcription_enabled=True,
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer()
)
)
)
tts = PlayHTTTSService(
user_id=os.getenv("PLAYHT_USER_ID"),
api_key=os.getenv("PLAYHT_API_KEY"),
voice_url="s3://voice-cloning-zero-shot/801a663f-efd0-4254-98d0-5c175514c3e8/jennifer/manifest.json",
)
tts = PlayHTTTSService(
user_id=os.getenv("PLAYHT_USER_ID"),
api_key=os.getenv("PLAYHT_API_KEY"),
voice_url="s3://voice-cloning-zero-shot/801a663f-efd0-4254-98d0-5c175514c3e8/jennifer/manifest.json",
)
llm = OpenAILLMService(
api_key=os.getenv("OPENAI_API_KEY"),
model="gpt-4o")
llm = OpenAILLMService(
api_key=os.getenv("OPENAI_API_KEY"),
model="gpt-4o")
messages = [
{
"role": "system",
"content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
},
]
messages = [
{
"role": "system",
"content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
},
]
tma_in = LLMUserResponseAggregator(messages)
tma_out = LLMAssistantResponseAggregator(messages)
tma_in = LLMUserResponseAggregator(messages)
tma_out = LLMAssistantResponseAggregator(messages)
pipeline = Pipeline([
transport.input(), # Transport user input
tma_in, # User responses
llm, # LLM
tts, # TTS
transport.output(), # Transport bot output
tma_out # Assistant spoken responses
])
pipeline = Pipeline([
transport.input(), # Transport user input
tma_in, # User responses
llm, # LLM
tts, # TTS
transport.output(), # Transport bot output
tma_out # Assistant spoken responses
])
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
transport.capture_participant_transcription(participant["id"])
# Kick off the conversation.
messages.append(
{"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMMessagesFrame(messages)])
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
transport.capture_participant_transcription(participant["id"])
# Kick off the conversation.
messages.append(
{"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMMessagesFrame(messages)])
runner = PipelineRunner()
runner = PipelineRunner()
await runner.run(task)
await runner.run(task)
if __name__ == "__main__":